Intel® Math Kernel Library for Deep Learning Networks: Part 1–Overview and Installation

Learn how to install and build the library components of the Intel MKL for Deep Neural Networks.
Автор: Bryan B. (Intel) Последнее обновление: 11.03.2019 - 13:17

Building Large-Scale Image Feature Extraction with BigDL at

This article shares the experience and lessons learned from Intel and JD teams in building a large-scale image feature extraction framework using deep learning on Apache Spark* and BigDL.
Автор: Jason Dai (Intel) Последнее обновление: 30.05.2019 - 15:56

Getting Started with Intel® Optimization for PyTorch* on Second Generation Intel® Xeon® Scalable Processors

Accelerate deep learning PyTorch* code on second generation Intel® Xeon® Scalable processor with Intel® Deep Learning Boost.
Автор: Nathan Greeneltch (Intel) Последнее обновление: 15.10.2019 - 16:50

Performance Comparison of OpenBLAS* and Intel® Math Kernel Library in R

Today, scientific and business industries collect large amounts of data, analyze them, and make decisions based on the outcome of the analysis. This paper compares the performance of Basic Linear Algebra Subprograms (BLAS), libraries OpenBLAS, and the Intel® Math Kernel Library (Intel® MKL).
Автор: Nguyen, Khang T (Intel) Последнее обновление: 15.10.2019 - 16:50